
2020 年 5 月 Journal on Communications May 2020
第 41 卷第 5 期 通 信 学 报 Vo l .41
No.5
基于改进的免疫克隆蛙跳算法的多约束 QoS 路由优化研究
卢毅,徐梦颖,周杰
(石河子大学信息科学与技术学院,新疆 石河子 832003)
摘 要:针对多约束路由选择问题,设计了数学模型并提出了一种改进的免疫克隆蛙跳算法。所提方法结合了免
疫克隆算法与传统蛙跳算法,在分组丢失率、链路带宽、时延抖动、时延、能量损耗条件的限制下,计算源节点
到终端节点的能量损耗,通过所提算法寻找一条能量损耗最小的路径。在仿真实验中,将所提算法与自适应遗传
算法、自适应蚁群算法进行了对比。实验结果表明,所提算法在一定程度上解决了多约束 QoS 单播路由优化
问题,与自适应遗传算法与自适应蚁群算法相比,所提算法避免了局部最优,有效地降低了数据在传输路径
上的能量损耗。
关键词:蛙跳算法;服务质量优化;路由优化;遗传算法;蚁群优化算法
中图分类号:TP212.6
文献标识码:A
doi: 10.11959/j.issn.1000−436x.2020102
Multi-constraints QoS routing optimization based on improved
immune clonal shuffled frog leaping algorithm
LU Yi, XU Mengying, ZHOU Jie
College of Information Science and Technology, Shihezi University, Shihezi 832003, China
Abstract: Aiming at the multi-constraint routing problem, a mathematical model was designed, and an improved immune
clonal shuffled frog leaping algorithm (IICSFLA) was proposed, which combined immune operator with traditional
SFLA. Under the constraints of bandwidth, delay, packet loss rate, delay jitter and energy cost, total energy cost from the
source node to the terminal node was computed. The proposed algorithm was used to find an optimal route with mini-
mum energy cost. In the simulation, the performance of IICSFLA with adaptive genetic algorithm and adaptive ant colo-
ny optimization algorithm was compared. Experimental results show that IICSFLA solves the problem of mul-
ti-constraints QoS unicast routing optimization. The proposed algorithm avoids local optimum and effectively reduces
energy loss of data on the transmission path in comparison with adaptive genetic algorithm and adaptive ant colony opti-
mization algorithm.
Key words: shuffled frog leaping algorithm, QoS optimization, routing optimization, genetic algorithm, ant colony opti-
mization algorithm
1 引言
随着无线通信技术的迅速发展,无线传感器
网络(WSN, wireless sensor network)已成为研究
热点之一。由于其低能耗、低成本、数据存储能
力强、无线通信能力强、自组织等特点,WSN 的
应用领域越来越广,包括智能家居、交通、农田
监测等
[1]
。
无线传感器网络由众多具备信号传输与计算
性能的传感器节点通过自组织网络的形式构成,其
收稿日期:2019-09-04;修回日期:2020-01-10
通信作者: 周杰,jiezhou@shzu.edu.cn
基金项目:兵团中青年科技创新领军人才计划基金资助项目(No.2018CB006)
Foundation Item: Corps Young and Middle-Aged Science and Technology Innovation Leadership Talents Project (No.2018CB006)